Cloud Retrieval and Cloud Type Detection from Himawari-8 Satellite Data Based on the Split Window Algorithm

Material type: 文書・図像類

Author: PURBANTORO, Babagほか

Publisher: Chiba University. Center for Environmental Remote Sensing

Publication date: 2016-11-21

Material Format: Digital

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Note (General)：: type:text[ABSTRACT]Cloud detection and cloud type classification yields basic information indispensable for meteorological as well as climate studies....

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Material Type: 文書・図像類
Title: Cloud Retrieval and Cloud Type Detection from Himawari-8 Satellite Data Based on the Split Window Algorithm
Author/Editor: PURBANTORO, Babag
AMINUDDIN, Jamrud
MANAGO, Naohiro
TOYOSHIMA, Koichi
JOSAPHAT, Tetuko Sri Sumantyo
KUZE, Hiroaki
Author Heading: PURBANTORO, Babag
AMINUDDIN, Jamrud
MANAGO, Naohiro
TOYOSHIMA, Koichi
JOSAPHAT, Tetuko Sri Sumantyo
KUZE, Hiroaki
Publication, Distribution, etc.: Chiba University. Center for Environmental Remote Sensing
Publication Date: 2016-11-21
Publication Date (W3CDTF): 2016-11-21
Periodical title: Proceedings of the CEReS international symposium = CEReS国際シンポジウム資料集
No. or year of volume/issue: 24
Volume: 24
Pages: 854-857
Text Language Code: eng
Target Audience: 一般
Note (General): type:text
[ABSTRACT]Cloud detection and cloud type classification yields basic information indispensable for meteorological as well as climate studies. Here we propose the use of Himawari-8 data. This satellite has been employed for operational use since July 2015, providing spectral data over 16 channels in visible (VIS), near-infrared (NIR) and thermal infrared (TIR) spectral regions. Also, high temporal resolution is available for both full disk (10 min) and Japanese archipelago (2.5 min). First, we test the traditional approach of the split- window algorithm using bands 15 and 16, centered at 12 and 13 μm, respectively, for the determination of cloud density. The brightness temperature difference (BTD) between two bands are derived on the basis of the Planck formula. The resultant threshold temperatures are 250 and 270 K for the discrimination of high, middle and low-level clouds. The BTD thresholds, on the other hand, are determined to be 5 and 11 K for distinguishing very thin, thin or thick clouds. The verification of cloud classification results will also be discussed.
Format (IMT): application/pdf
Source: https://opac.ll.chiba-u.jp/da/curator/107917/ceresIntlSympo-24-P854.pdf
https://opac.ll.chiba-u.jp/da/curator/107917/ceresIntlSympo-24-P854.pdf
Access Restrictions: 限定公開
Data Provider (Database): 国立情報学研究所 : 学術機関リポジトリデータベース（IRDB）（機関リポジトリ）
https://irdb.nii.ac.jp
Original Data Provider (Database): 千葉大学 : 千葉大学学術成果リポジトリ